Integrated BIM tools, including Revit, AutoCAD, and Civil 3D
Professional CAD/CAM tools built on Inventor and AutoCAD
Any referenced datasets can be downloaded from "Module downloads" in the module overview.
Transcript
00:03
We will now discuss the benefits and risks of generative AI.
00:07
The first benefit is that generative AI has
00:10
the ability to understand and generate human-like text.
00:14
It generates diverse and innovative content,
00:17
including text,
00:18
images and designs.
00:20
This can enhance creativity and foster innovation in fields such as engineering,
00:25
product development,
00:26
architecture,
00:27
art,
00:27
and marketing.
00:29
It can also improve efficiency and versatility by automating repetitive tasks
00:34
and reducing manual efforts and tasks such as content generation,
00:38
data analysis,
00:39
and even code generation.
00:41
Generative AI streamlines data augmentation
00:44
by producing realistic synthetic data,
00:47
enabling more comprehensive model training and enhancing the
00:50
accuracy and generalization of data analysis tasks.
00:54
The advanced language understanding of generative AI allows for more
00:58
natural and context aware interactions in applications like chatbots,
01:03
virtual assistants and customer support.
01:06
Generative AI also facilitates language translation with improved accuracy,
01:11
which can support global communication and remove language barriers.
01:15
The
01:15
last benefit of generative AI is its ability to enable personalized
01:20
experiences by tailoring content or products based on individual preferences,
01:25
which enhances user engagement and satisfaction.
01:29
There are also risks associated with using generative AI that must be considered.
01:34
The first of these is accuracy.
01:37
Generative AI models can produce information that seems accurate
01:41
but is actually false.
01:43
The models do not have the ability to use context and judgment the way humans do.
01:49
These models are also trained on massive amounts
01:52
of data from which they create generalizations,
01:55
so they may provide inaccurate responses to specific inputs.
01:59
For this reason,
02:01
users should use external verification methods.
02:04
The next risk is potentially biased outputs.
02:08
Generative AI models learn from large data sets that may contain
02:12
biases which could cause them to generate misleading or biased information.
02:18
Privacy concerns are also a risk of generative AI
02:22
as models could inadvertently generate sensitive or personally identifiable
02:27
information that was present in its training data.
02:30
Malicious use of generative AI can be a risk if the tool is
02:33
being used to create realistic looking fake
02:36
content for misinformation or phishing attempts.
02:39
The last risk is copyright infringement.
02:42
Currently no one owns copyrights on AI generated works,
02:47
however,
02:48
AI programs may infringe copyright by
02:51
generating outputs that resemble existing works.
02:55
Also determining the ownership and attribution
02:57
of generated content may become challenging,
03:01
especially if the AI model combines elements from various sources.
03:05
Ensuring responsible deployment and addressing these risks are
03:09
crucial for the ethical use of these technologies.
Video transcript
00:03
We will now discuss the benefits and risks of generative AI.
00:07
The first benefit is that generative AI has
00:10
the ability to understand and generate human-like text.
00:14
It generates diverse and innovative content,
00:17
including text,
00:18
images and designs.
00:20
This can enhance creativity and foster innovation in fields such as engineering,
00:25
product development,
00:26
architecture,
00:27
art,
00:27
and marketing.
00:29
It can also improve efficiency and versatility by automating repetitive tasks
00:34
and reducing manual efforts and tasks such as content generation,
00:38
data analysis,
00:39
and even code generation.
00:41
Generative AI streamlines data augmentation
00:44
by producing realistic synthetic data,
00:47
enabling more comprehensive model training and enhancing the
00:50
accuracy and generalization of data analysis tasks.
00:54
The advanced language understanding of generative AI allows for more
00:58
natural and context aware interactions in applications like chatbots,
01:03
virtual assistants and customer support.
01:06
Generative AI also facilitates language translation with improved accuracy,
01:11
which can support global communication and remove language barriers.
01:15
The
01:15
last benefit of generative AI is its ability to enable personalized
01:20
experiences by tailoring content or products based on individual preferences,
01:25
which enhances user engagement and satisfaction.
01:29
There are also risks associated with using generative AI that must be considered.
01:34
The first of these is accuracy.
01:37
Generative AI models can produce information that seems accurate
01:41
but is actually false.
01:43
The models do not have the ability to use context and judgment the way humans do.
01:49
These models are also trained on massive amounts
01:52
of data from which they create generalizations,
01:55
so they may provide inaccurate responses to specific inputs.
01:59
For this reason,
02:01
users should use external verification methods.
02:04
The next risk is potentially biased outputs.
02:08
Generative AI models learn from large data sets that may contain
02:12
biases which could cause them to generate misleading or biased information.
02:18
Privacy concerns are also a risk of generative AI
02:22
as models could inadvertently generate sensitive or personally identifiable
02:27
information that was present in its training data.
02:30
Malicious use of generative AI can be a risk if the tool is
02:33
being used to create realistic looking fake
02:36
content for misinformation or phishing attempts.
02:39
The last risk is copyright infringement.
02:42
Currently no one owns copyrights on AI generated works,
02:47
however,
02:48
AI programs may infringe copyright by
02:51
generating outputs that resemble existing works.
02:55
Also determining the ownership and attribution
02:57
of generated content may become challenging,
03:01
especially if the AI model combines elements from various sources.
03:05
Ensuring responsible deployment and addressing these risks are
03:09
crucial for the ethical use of these technologies.
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